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Think 2018: Our favorite highlights from Monday

IBM Big Data Hub

Think 2018 is the biggest IBM conference of the year covering all things tech. And, to be sure you don't miss a moment, here are highlights from Monday, March 19, the first day of the event

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Think 2018: Our favorite highlights from Tuesday

IBM Big Data Hub

The excitement, insights and innovation at Think 2018 is truly astounding. Today we heard from IBM Chairman, President and CEO, Ginni Rometty, plus industry leaders and clients who are transforming whole business sectors

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Think 2018: Our favorite highlights from Thursday

IBM Big Data Hub

Hard to believe we've arrived at the last day of Think 2018. From keynotes to panels, informal collaborations and learning sessions, we've witnessed first-hand the excitement that conversations about data and analytics bring to business

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A List Of Business Analysis Events For 2018

BA Learnings

If you’re ready for socializing and networking or just looking for professional development opportunities, here are some business analysis events to get you started in 2018. ProjectWorld*BusinessAnalystWorld holds this year from June 4-7, 2018 in Toronto and is reputed to be the largest series of conferences for project managers and business analysts in North America. Explore the event scheduled to hold in Santa Barbara, California from April 17 - April 19, 2018.

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Defining data science in 2018

Data Science and Beyond

This article is a short summary of my understanding of the definition of data science in 2018. I got my first data science job in 2012, the year Harvard Business Review announced data scientist to be the sexiest job of the 21st century. Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics.

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Think 2018: Our favorite highlights from Wednesday

IBM Big Data Hub

Think 2018 is in full swing. We’re inspired hearing from leaders across industries using analytics to transform their business. And we’re thrilled to take part in conversations about data science, machine learning, AI and much more. Here are some highlights from Wednesday at Think

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Discovering best practices for IoT at Think 2018

IBM Big Data Hub

Think 2018 in Las Vegas was a record breaking event, where tens of thousands of attendees gathered to talk with one another and share their experiences. Visionary speakers and experts shared their solutions for some of the world’s most daunting challenges

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Highlights from JupyterCon in New York 2018

O'Reilly on Data

Watch keynotes covering Jupyter's role in business, data science, higher education, open source, journalism, and other domains, from JupyterCon in New York 2018. Jupyter trends in 2018. Paco Nathan shares a few unexpected things that emerged in Jupyter in 2018. Watch " Jupyter trends in 2018.". Watch " Sea change: What happens when Jupyter becomes pervasive at a university? ". --> Continue reading Highlights from JupyterCon in New York 2018

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Five Strategies for Slaying the Data Puking Dragon.

Occam's Razor

If you bring sharp focus, you increase chances of attention being diverted to the right places. That in turn will drive smarter questions, which will elicit thoughtful answers from available data. The result will be data-influenced actions that result in a long-term strategic advantage. It all starts with sharp focus. Consider these three scenarios…. Your boss is waiting for you to present results on quarterly marketing performance, and you have 75 dense slides.

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What's in store for a CDO at Think 2018

IBM Big Data Hub

When you wake up, the last thing you want to ask yourself is, “What did my data do last night?” CDOs who find themselves asking that question can put a stop to it on March 19. IBM is bringing experts and leaders across data governance and integration to the annual Think conference

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Highlights from the Strata Data Conference in New York 2018

O'Reilly on Data

Watch " Black box: How AI will amplify the best and worst of humanity.". --> Continue reading Highlights from the Strata Data Conference in New York 2018 Watch highlights from expert talks covering data science, machine learning, algorithmic accountability, and more. People from across the data world are coming together in New York for the Strata Data Conference. Below you'll find links to highlights from the event. The future of data warehousing.

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Today at Think 2018: What you can’t miss Thursday

IBM Big Data Hub

Hard to believe, but we’ve arrived at the final day of Think 2018. It’s been thrilling to be part of the energy flowing through the Cloud & Data Campus. We’ve seen an unprecedented level of engagement around analytics and the future of data-driven decision-making. But we’re not done yet. Here are our top picks for analytics pros today

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What's in store for a data scientist at Think 2018

IBM Big Data Hub

Getting the most from a data science agenda requires more than data scientists. At Think, you’ll learn to view data science as a team sport, involving multiple roles and appropriate tools that help organizations tap into the benefits data science can bring wherever the business opportunity is

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Today at Think 2018: What you can’t miss Monday

IBM Big Data Hub

We’re live at Think 2018. If you’re joining us in Las Vegas, welcome to the biggest IBM event of the year. You’re about to experience a whirlwind of analytics keynotes, panels, demos, and more

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What's in store for a FOPM pro at Think 2018

IBM Big Data Hub

Almost any kind of finance and operational performance management (FOPM) professional, from VPs of finance to analysts and others, can learn a lot at Think 2018

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Hybrid use cases to dominate machine learning in 2018, part 1

IBM Big Data Hub

Big Data and Analytics Hub spoke with IBM Distinguished Engineer John Thomas (@johnjaithomas) about some of the importance of focusing on information architecture to make algorithms meet enterprise needs, as well as how machine learning can most effectively be applied in hybrid scenarios in 2018

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Consolidation around Cognos 11.1 and other news from IBM Analytics University

David Menninger's Analyst Perspectives

For the full breakdown of IBM's Analytics University 2018, and my analysis of all the largest announcements, watch my latest hot take. IBM's Analytics University (held in both Miami and Stockholm) brought about some large changes. Big announcements this year included a consolidation of IBM's Watson Analytics into Cognos 11.1, helping provide some clarity to their analytics offerings, along with new visualizations and better data preparation.

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What's in store for an enterprise architect at Think 2018

IBM Big Data Hub

That’s exactly why they need to set aside a few days in March to attend Think 2018 in Las Vegas With businesses requiring foresight into emerging technologies and relying on nimble responses, successful architects must know how to get the most of their data infrastructure and build for the future.

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Hybrid use cases to dominate machine learning in 2018, part 2

IBM Big Data Hub

Big Data and Analytics Hub spoke with IBM Distinguished Engineer John Thomas (@johnjaithomas) about some of the importance of tuning information architecture to make algorithms meet enterprise needs, as well as how machine learning can most effectively be applied in hybrid scenarios in 2018

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Strata Data San Jose March 2018 Musings

Sanjeev Mohan

Ladies and Gentlemen, we have a new buzz word for 2018: Operationalization ! The post Strata Data San Jose March 2018 Musings appeared first on Sanjeev Mohan I attended this year’s edition of Strata Data show last week in San Jose. Last year when I attended the show, it was still called Strata Hadoop. Interestingly, if last year many companies were trying to distance themselves from Hadoop, this year I witnessed outright hostility towards it.

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News and Announcements from Tableau and TC18

David Menninger's Analyst Perspectives

For the full breakdown of Tableau User Conference 2018, and my analysis of all the largest announcements, watch my hot take video. Once again I attended Tableau's Users Conference, along with 17,000 other attendees, affectionately self-referred to as "data nerds".

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Top BOB Blog Posts of 2018: Data Science, Machine Learning and the Net Promoter Score

Business Over Broadway

All of my top blog posts of 2018 (most reads) are all related to data science, with posts that address the practice of data science, artificial intelligence and machine learning tools and methods that are commonly used and even a post on the problems with the Net Promoter Score claims. Below are my top 10 blog posts of 2018: Favorite Data Science Blogs, Podcasts and Newsletters. Looking ahead to 2018, data professionals are most interested in learning deep learning (41%).

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Will data management's trends collide or converge in 2018?

IBM Big Data Hub

While the proliferation of data will be readily apparent, deciding what to do in response will be less straightforward. The majority of workloads currently sit in traditional, on-premises environments but we’ll see many of them move to private and public clouds over the next over the next five years

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Today at Think 2018: What you can’t miss Wednesday

IBM Big Data Hub

Are you ready for another exciting day of Think 2018? There’s a big day planned for you at the Cloud & Data Campus and we’re here to help you navigate the many exciting sessions. Here are our top analytics picks of the day

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Reflections on the 2018 state of information management

IBM Big Data Hub

“Content management” — at least as traditionally defined — is no longer the straw that stirs the process drink. It’s a key element, yes. It’s an important set of tools in the enterprise toolkit, yes. But it is not the only game in process town

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Today at Think 2018: What you can’t miss Tuesday

IBM Big Data Hub

The second day of Think 2018 is here, and there’s an abundance of things to see and do at the Cloud & Data Campus. Here are the not-to-miss Think 2018 keynote speeches, demos, panels, training labs and other hands-on activities for Tuesday, March 20, both at the event and by tuning in online

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What Business Analysts Can Learn From Swiss Cheese

BA Learnings

Swiss cheese has holes in various places on different slices of cheese when you cut it up. Let’s imagine these holes reflect weaknesses in the system where mistakes can pass through, afterall no system is perfect. One mistake passing through a hole in one slice of cheese might remain unnoticed and not lead to a business catastrophe, if it's corrected.

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Deep automation in machine learning

O'Reilly on Data

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

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What's in store for a business analytics pro at Think 2018

IBM Big Data Hub

Whether you’re a developer, manager of an IT department or almost any other kind of business intelligence professional, Think 2018 has something for you

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The Best Fails of 2018

Bruno Aziza

What an incredible year. I’m no financial expert. But as a market observer, I have noted a fair amount of #fails this year. Here are at least 3 that I thought would be worth recapping. I’m sure I’ve missed a few. Feel free to tweet me at @brunoaziza for comments and suggestions

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Meta-Learning For Better Machine Learning

Rocket-Powered Data Science

Workshop on Meta-Learning (MetaLearn 2018). In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. An example of a cold start problem is k -Means Clustering, where the number of clusters k in the data set is not known in advance, and the locations of those clusters in feature space ( i.e., the cluster means) are not known either.

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Business Goals for 2019: Looking back over 2018 and forward

Jen Stirrup

How was 2018 for you? Current Status for 2018: I have partners who help me to deliver effectively. Current Status for 2018: 50% repeat customers with 50% new customers generated by word–of-mouth from previous customers. Current Status for 2018: I started more business networking last year but it tailed off in February. Current Status for 2018: I got involved with DataKind. December is a great time for setting personal and business goals for next year.

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Building tools for enterprise data science

O'Reilly on Data

The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science. In this episode of the Data Show , I spoke with Vitaly Gordon , VP of data science and engineering at Salesforce. As the use of machine learning becomes more widespread, we need tools that will allow data scientists to scale so they can tackle many more problems and help many more people.

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Confirmation Bias: What BAs Can Learn From Data Scientists

BA Learnings

When we have a strong belief about something or a bias towards a particular opinion, we consciously or unconsciously seek out evidence that validates what we already believe. When we come across contrary evidence, our default behaviour is to ignore it, diminish it or in some cases, conclude that it’s wrong prematurely without exploring its merits. This behaviour is due to a cognitive bias known as confirmation bias.

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Managing risk in machine learning

O'Reilly on Data

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Let’s begin by looking at the state of adoption.

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Tesla CEO Musk's anti-union tweet from 2018 must be deleted: U.S. labor board

DataFloq

(Reuters) - Tesla Inc Chief Executive Officer Elon Musk's 2018 tweet threatening employees would lose their stock options if they formed a union was illegal and should be deleted, the U.S.

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How social science research can inform the design of AI systems

O'Reilly on Data

The O’Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems. In this episode of the Data Show , I spoke with Jacob Ward , a Berggruen Fellow at Stanford University. Ward has an extensive background in journalism, mainly covering topics in science and technology, at National Geographic , Al Jazeera, Discovery Channel, BBC, Popular Science , and many other outlets.

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Recapping the IBM Chief Data Officer Strategy Summit Spring 2018

IBM Big Data Hub

Building on the success of the IBM Chief Data Officer Strategy Summit Fall 2017, the IBM Chief Data Officer Summit Spring 2018 took place 1 - 2 May in San Francisco. We've collected a full social recap in the below Twitter Moment, as well as interviews and keynote videos for you to peruse

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Recent top-selling books in AI and Machine Learning

Rocket-Powered Data Science

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The Market of Data at Strata

David Menninger's Analyst Perspectives

In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event , the focus was largely on machine learning and artificial intelligence (AI). That theme continued this year, but my impression of the event was of a community looking to get value out of data regardless of the technology being used to manage that data.

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Trends in data, machine learning, and AI

O'Reilly on Data

The O’Reilly Data Show Podcast: Ben Lorica looks ahead at what we can expect in 2019 in the big data landscape. For the end-of-year holiday episode of the Data Show , I turned the tables on Data Show host Ben Lorica to talk about trends in big data, machine learning, and AI, and what to look for in 2019. Lorica also showcased some highlights from our upcoming Strata Data and Artificial Intelligence conferences. Continue reading Trends in data, machine learning, and AI

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Industry Pulse September 2018 Highlights

DataRobot Blog

by Jen Underwood. Long time, no news summaries…what happened? I’ll share the scoop on that soon. In the meantime, Cloudera and Hortonworks announced a merger that was really “big” news yesterday. That merger. Read More. Tableau Big Data & IoT Industry Perspective Predictive Analytics Spotfire BI & Analytics Artificial Intelligence

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Why it’s hard to design fair machine learning models

O'Reilly on Data

The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness. In this episode of the Data Show , I spoke with Sharad Goel , assistant professor at Stanford, and his student Sam Corbett-Davies. They recently wrote a survey paper, “A Critical Review of Fair Machine Learning,” where they carefully examined the standard statistical tools used to check for fairness in machine learning models.